In Silico Modeling and Identification of Novel Epitopes-based Vaccine of M polyprotein (Gn/Gc) against Schmallenberg Virus for Ruminants

Research Paper (postgraduate) from the year 2016 in the subject Computer Science - Bioinformatics, , language: English, abstract: Schmallenberg (SBV) is a new virus of the Bunyaviridae family within the genus Orthobunyavirus. The viral infection causes mild clinical signs: fever, reduced milk production and diarrhea, as well as considerable economic loss.There is currently no treatment or vaccine for infected animals. We aimed to design a peptide vaccine using an Immunoinformatics approach to stimulate the immune system and reduce the potentially negative effects of using live vaccines.In this study, a total of 47 strains of complete M polyprotein sequence (Gn/NSm/GC) and 61 strains of nonstructural protein in S segment (NSs) of Schmallenberg virus which were chosen for this study were taken from NCBI. Potentially continuous B and T cell epitopes were predicted using tools from immune epitope data base analysis resource (IEDB-AR).We found that Gn and Gc regions of M polyprotein in SBV were clearly suitable and could be used for the preparation of immunological constructs. Our studies suggest that: B cell epitope 764QQQACSS770 and CTL epitopes 251YMYNKYFKL259, 46SECCVKDDI54 and 234IVYVFIPIF242 could be used as a potential vaccine candidate against SBV.We consider this study distinctive because no research ever dealt with peptide-based vaccines on virulent strains of SBV using an in silico approach.

Autorentext

Marwa Mohamed Osman was awarded MS.c. degree in Microbiology from Sudan Academy of Sciences. She is an Associate Researcher at Africa city of Technology,Sudan-Khartoum. She has published more than 10 papers in word renowned journals. She has been member of American society of Clinical Pathology (ASCPi) as International Medical Scientist.